Advances in Longitudinal HCI Research
Date Issued
2021
DOI
10.1007/978-3-030-67322-2
Abstract
Longitudinal studies have traditionally been seen as too cumbersome and labor-intensive to be of much use in research on Human-Computer Interaction (HCI). However, recent trends in market, legislation, and the research questions we address, have highlighted the importance of studying prolonged use, while technology itself has made longitudinal research more accessible to researchers across different application domains.
Aimed as an educational resource for graduate students and researchers in HCI, this book brings together a collection of chapters, addressing theoretical and methodological considerations, and presenting case studies of longitudinal HCI research. Among others, the authors:
discuss the theoretical underpinnings of longitudinal HCI research, such as when a longitudinal study is appropriate, what research questions can be addressed and what challenges are entailed in different longitudinal research designs
reflect on methodological challenges in longitudinal data collection and analysis, such as how to maintain participant adherence and data reliability when employing the Experience Sampling Method in longitudinal settings, or how to cope with data collection fatigue and data safety in applications of autoethnography and autobiographical design, which may span from months to several years
present a number of case studies covering different topics of longitudinal HCI research, from “slow technology”, to self-tracking, to mid-air haptic feedback, and crowdsourcing.
Aimed as an educational resource for graduate students and researchers in HCI, this book brings together a collection of chapters, addressing theoretical and methodological considerations, and presenting case studies of longitudinal HCI research. Among others, the authors:
discuss the theoretical underpinnings of longitudinal HCI research, such as when a longitudinal study is appropriate, what research questions can be addressed and what challenges are entailed in different longitudinal research designs
reflect on methodological challenges in longitudinal data collection and analysis, such as how to maintain participant adherence and data reliability when employing the Experience Sampling Method in longitudinal settings, or how to cope with data collection fatigue and data safety in applications of autoethnography and autobiographical design, which may span from months to several years
present a number of case studies covering different topics of longitudinal HCI research, from “slow technology”, to self-tracking, to mid-air haptic feedback, and crowdsourcing.